EEG Signal Classification Based On Fuzzy Classifiers

نویسندگان

چکیده

Electroencephalogram (EEG) signal classification is used in many applications. Typically, this implemented based on methods which consist of two steps. These steps are known as the step preprocessing and classification. The transforms initial into attributes. According to several studies, transformation can result loss some useful information and, consequently, formed attributes uncertain. This be taken account if fuzzy classifiers at itself. EEG needs one more procedure preprocessing. fuzzification. An approach for considered article. evaluated classifiers: decision tree random Forest. accuracy 99.5% 99.3% forest. comparison with similar studies non-fuzzy indicates that effective tool have best accuracy.

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ژورنال

عنوان ژورنال: IEEE Transactions on Industrial Informatics

سال: 2022

ISSN: ['1551-3203', '1941-0050']

DOI: https://doi.org/10.1109/tii.2021.3084352